De Deyne Simon, Navarro Daniel J, Perfors Amy, Storms Gert
Computational Cognitive Science Lab, School of Psychology, University of Adelaide.
University of New South Wales.
J Exp Psychol Gen. 2016 Sep;145(9):1228-54. doi: 10.1037/xge0000192.
Similarity plays an important role in organizing the semantic system. However, given that similarity cannot be defined on purely logical grounds, it is important to understand how people perceive similarities between different entities. Despite this, the vast majority of studies focus on measuring similarity between very closely related items. When considering concepts that are very weakly related, little is known. In this article, we present 4 experiments showing that there are reliable and systematic patterns in how people evaluate the similarities between very dissimilar entities. We present a semantic network account of these similarities showing that a spreading activation mechanism defined over a word association network naturally makes correct predictions about weak similarities, whereas, though simpler, models based on direct neighbors between word pairs derived using the same network cannot. (PsycINFO Database Record
相似性在组织语义系统中起着重要作用。然而，鉴于相似性不能仅仅基于逻辑来定义，了解人们如何感知不同实体之间的相似性就很重要。尽管如此，绝大多数研究都集中在测量密切相关项目之间的相似性。当考虑非常弱相关的概念时，我们知之甚少。在本文中，我们展示了4个实验，表明人们在评估非常不相似实体之间的相似性时存在可靠且系统的模式。我们提出了一个关于这些相似性的语义网络解释，表明在词联想网络上定义的扩散激活机制自然地对弱相似性做出了正确预测，而基于使用同一网络导出的词对之间直接邻域的模型虽然更简单，但却不能。（PsycINFO数据库记录）
